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Record W3102463437 · doi:10.3390/ijerph17228469

Research Trends in Green Product for Environment: A Bibliometric Perspective

2020· review· en· W3102463437 on OpenAlexaff
Amit Kumar Bhardwaj, Arunesh Garg, Shri Ram, Yuvraj Gajpal

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2020
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSustainabilityGreen marketingScopusBusinessProduct (mathematics)MarketingLoyaltyVariety (cybernetics)Sustainable developmentEnvironmental economicsPolitical scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

The term "green products" is used commonly to describe the products that seek to protect or enhance the environment during production, use, or disposal by conserving resources and minimizing the use of toxic agents, pollution, and waste. Hence, green products offer potential benefits to the environment and human health. Therefore, environmentally conscious consumers have shown an enhanced inclination for them. Consumer preferences, environmental activism, and stringent regulations have forced sustainability-oriented firms to shift their focus to producing green products. The present study uses bibliometric tools and various indicators to discern research progress in the field of green products over the period 1964-2019. Further, VOSviewer software is applied to map the main trends. A total of 1619 publications during the study period were extracted from the SCOPUS database using different keywords related to the green products. The data analysis indicates that the field of green products has experienced significant growth since 1964, especially in the last 14 years. In terms of publications and citations, the United States is the leading country. The field of research concerning green products has evolved from the early debates on sustainable design, green marketing, sustainable development, and sustainability. The topic seems to be advancing into a variety of green themes related to consumer trust and purchase intentions, branding and loyalty, and environmental and health consciousness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0490.013
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.198
GPT teacher head0.458
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations92
Published2020
Admission routes1
Has abstractyes

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